└── README.md /README.md: -------------------------------------------------------------------------------- 1 | # really-awesome-gan 2 | A list of papers and other resources on Generative Adversarial (Neural) Networks. 3 | This site is maintained by Holger Caesar. 4 | To complement or correct it, please contact me at holger-at-it-caesar.com or visit [it-caesar.com](http://www.it-caesar.com). Also checkout [really-awesome-semantic-segmentation](https://github.com/nightrome/really-awesome-semantic-segmentation) and our [COCO-Stuff dataset](https://github.com/nightrome/cocostuff). 5 | 6 | **NOTE:** Despite the enormous interest in this cite (~3000 visitors per month), I will no longer add new papers starting from November 2017. I feel that GANs have come from an exotic topic to the mainstream and an exhaustive list of all GAN papers is no more feasible or useful. However, I invite other people to continue this effort and reuse my list. 7 | 8 | ## Contents 9 | - [Recommendations](#recommendations) 10 | - [Workshops](#workshops) 11 | - [Tutorials & Workshops & Blogs](#tutorials--workshops--blogs) 12 | - [Videos](#videos) 13 | - [Code](#code) 14 | - [Papers](#papers) 15 | - [Overview](#overview) 16 | - [Theory & Machine Learning](#theory--machine-learning) 17 | - [Applied Vision](#applied-vision) 18 | - [Applied Other](#applied-other) 19 | - [Humor](#humor) 20 | 21 | ## Recommendations 22 | 32 | 33 | # Tutorials & Workshops & Blogs 34 | - Columbia Advanced Machine Learning Seminar 35 | - New Progress on GAN Theory and Practice [[Blog]](https://casmls.github.io/general/2017/04/13/gan.html) 36 | - Implicit Generative Models — What are you GAN-na do? [[Blog]](https://casmls.github.io/general/2017/05/24/ligm.html) 37 | - How to Train a GAN? Tips and tricks to make GANs work [[Blog]](https://github.com/soumith/ganhacks) 38 | - NIPS 2016 Tutorial: Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1701.00160) 39 | - NIPS 2016 Workshop on Adversarial Training [[Web]](https://sites.google.com/site/nips2016adversarial/) [[Blog]](http://www.inference.vc/my-summary-of-adversarial-training-nips-workshop/) 40 | - On the intuition behind deep learning & GANs — towards a fundamental understanding [[Blog]](https://blog.waya.ai/introduction-to-gans-a-boxing-match-b-w-neural-nets-b4e5319cc935) 41 | - OpenAI - Generative Models [[Blog]](https://openai.com/blog/generative-models/) 42 | - SimGANs - a game changer in unsupervised learning, self driving cars, and more [[Blog]](https://blog.waya.ai/simgans-applied-to-autonomous-driving-5a8c6676e36b) 43 | - Deep Diving into GANs: from theory to production (EuroScipy 2018) [[GitHub]](https://github.com/zurutech/gans-from-theory-to-production) 44 | 45 | # Books 46 | - GANs in Action: Deep learning with Generative Adversarial Networks [[Book]](https://www.manning.com/books/gans-in-action) 47 | 48 | # Videos 49 | - Generative Adversarial Networks by Ian Goodfellow [[Video]](https://channel9.msdn.com/Events/Neural-Information-Processing-Systems-Conference/Neural-Information-Processing-Systems-Conference-NIPS-2016/Generative-Adversarial-Networks) 50 | - Tutorial on Generative Adversarial Networks by Mark Chang [[Video]](https://www.youtube.com/playlist?list=PLeeHDpwX2Kj5Ugx6c9EfDLDojuQxnmxmU) 51 | - Deep Diving into GANs: From Theory to Production (EuroSciPy 2018) by Michele De Simoni, Paolo Galeone [[Video]](https://www.youtube.com/watch?v=CePrdabdtxw) 52 | 53 | # Code 54 | - Cleverhans: A library for benchmarking vulnerability to adversarial examples [[Code]](https://github.com/openai/cleverhans) [[Blog]](http://cleverhans.io/) 55 | - Generative Adversarial Networks (GANs) in 50 lines of code (PyTorch) [[Blog]](https://medium.com/@devnag/generative-adversarial-networks-gans-in-50-lines-of-code-pytorch-e81b79659e3f) [[Code]](https://github.com/devnag/pytorch-generative-adversarial-networks) 56 | - Generative Models: Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow [[Code]](https://github.com/wiseodd/generative-models) 57 | - Reproduction of the GANs paper (MNIST) in 100 lines of PyTorch code [[Blog]](https://papers-100-lines.medium.com/generative-adversarial-networks-in-100-lines-of-code-516f09d1790a) [[Code]](https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code/tree/main/Generative_Adversarial_Networks) 58 | - Reproduction of results from the paper *Conditional Generative Adversarial Nets* in 100 lines of PyTorch code [[Code]](https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code/tree/main/Conditional_Generative_Adversarial_Nets) 59 | - Reproduction of results from the paper *Improved Techniques for Training GANs* in 100 lines of PyTorch code [[Code]](https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code/tree/main/Improved_Techniques_for_Training_GANs) 60 | - Reproduction of results from the *LSGAN* paper in 100 lines of PyTorch code [[Code]](https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code/tree/main/Least_Squares_Generative_Adversarial_Networks) 61 | - Reproduction of results from the *WGAN* paper in 100 lines of PyTorch code [[Code]](https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code/tree/main/Wasserstein_GAN) 62 | - Reproduction of results from the *pix2pix* paper in 100 lines of PyTorch code [[Code]](https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code/tree/main/Image_to_Image_Translation_with_Conditional_Adversarial_Nets) 63 | 64 | # Papers 65 | ## Overview 66 | - Generative Adversarial Networks: An Overview [[arXiv]](https://arxiv.org/abs/1710.07035) 67 | 68 | ## Theory & Machine Learning 69 | - A Classification-Based Perspective on GAN Distributions [[arXiv]](https://arxiv.org/abs/1711.00970) 70 | - A Connection between Generative Adversarial Networks, Inverse Reinforcement Learning, and Energy-Based Models [[arXiv]](https://arxiv.org/abs/1611.03852) 71 | - A General Retraining Framework for Scalable Adversarial Classification [[Paper]](https://c4209155-a-62cb3a1a-s-sites.googlegroups.com/site/nips2016adversarial/WAT16_paper_2.pdf) 72 | - Activation Maximization Generative Adversarial Nets [[arXiv]](https://arxiv.org/abs/1703.02000) 73 | - AdaGAN: Boosting Generative Models [[arXiv]](https://arxiv.org/abs/1701.02386) 74 | - Adversarial Autoencoders [[arXiv]](https://arxiv.org/abs/1511.05644) 75 | - Adversarial Discriminative Domain Adaptation [[arXiv]](https://arxiv.org/abs/1702.05464) 76 | - Adversarial Generator-Encoder Networks [[arXiv]](https://arxiv.org/pdf/1704.02304.pdf) 77 | - Adversarial Feature Learning [[arXiv]](https://arxiv.org/abs/1605.09782) [[Code]](https://github.com/wiseodd/generative-models) 78 | - Adversarially Learned Inference [[arXiv]](https://arxiv.org/abs/1606.00704) [[Code]](https://github.com/wiseodd/generative-models) 79 | - AE-GAN: adversarial eliminating with GAN [[arXiv]](https://arxiv.org/abs/1707.05474) 80 | - An Adversarial Regularisation for Semi-Supervised Training of Structured Output Neural Networks [[arXiv]](https://arxiv.org/abs/1702.02382) 81 | - APE-GAN: Adversarial Perturbation Elimination with GAN [[arXiv]](https://arxiv.org/abs/1707.05474) 82 | - Associative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1611.06953) 83 | - Autoencoding beyond pixels using a learned similarity metric [[arXiv]](https://arxiv.org/abs/1512.09300) 84 | - Bayesian Conditional Generative Adverserial Networks [[arXiv]](https://arxiv.org/abs/1706.05477) 85 | - Bayesian GAN [[arXiv]](https://arxiv.org/abs/1705.09558) 86 | - BEGAN: Boundary Equilibrium Generative Adversarial Networks [[Paper]](https://c4209155-a-62cb3a1a-s-sites.googlegroups.com/site/nips2016adversarial/WAT16_paper_4.pdf) [[arXiv]](https://arxiv.org/abs/1703.10717) [[Code]](https://github.com/wiseodd/generative-models) 87 | - Binary Generative Adversarial Networks for Image Retrieval [[arXiv]](https://arxiv.org/abs/1708.04150) 88 | - Boundary-Seeking Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1702.08431) [[Code]](https://github.com/wiseodd/generative-models) 89 | - CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training [[arXiv]](https://arxiv.org/abs/1709.02023) 90 | - Class-Splitting Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1709.07359) 91 | - Comparison of Maximum Likelihood and GAN-based training of Real NVPs [[arXiv]](https://arxiv.org/abs/1705.05263) 92 | - Conditional CycleGAN for Attribute Guided Face Image Generation [[arXiv]](https://arxiv.org/abs/1705.09966) 93 | - Conditional Generative Adversarial Nets [[arXiv]](https://arxiv.org/abs/1411.1784) [[Code]](https://github.com/wiseodd/generative-models) 94 | - Connecting Generative Adversarial Networks and Actor-Critic Methods [[Paper]](https://c4209155-a-62cb3a1a-s-sites.googlegroups.com/site/nips2016adversarial/WAT16_paper_1.pdf) 95 | - Continual Learning in Generative Adversarial Nets [[arXiv]](https://arxiv.org/abs/1705.08395) 96 | - C-RNN-GAN: Continuous recurrent neural networks with adversarial training [[arXiv]](https://arxiv.org/abs/1611.09904) 97 | - CM-GANs: Cross-modal Generative Adversarial Networks for Common Representation Learning [[arXiv]](https://arxiv.org/abs/1710.05106) 98 | - Cooperative Training of Descriptor and Generator Networks [[arXiv]](https://arxiv.org/abs/1609.09408) 99 | - Coupled Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1606.07536) [[Code]](https://github.com/wiseodd/generative-models) 100 | - Dualing GANs [[arXiv]](https://arxiv.org/abs/1706.06216) 101 | - Deep and Hierarchical Implicit Models [[arXiv]](https://arxiv.org/abs/1702.08896) 102 | - Energy-based Generative Adversarial Network [[arXiv]](https://arxiv.org/abs/1609.03126) [[Code]](https://github.com/wiseodd/generative-models) 103 | - Explaining and Harnessing Adversarial Examples [[arXiv]](https://arxiv.org/abs/1412.6572) 104 | - Flow-GAN: Bridging implicit and prescribed learning in generative models [[arXiv]](https://arxiv.org/abs/1705.08868) 105 | - f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization [[arXiv]](https://arxiv.org/abs/1606.00709) [[Code]](https://github.com/wiseodd/generative-models) 106 | - Gang of GANs: Generative Adversarial Networks with Maximum Margin Ranking [[arXiv]](https://arxiv.org/abs/1704.04865) 107 | - Generalization and Equilibrium in Generative Adversarial Nets (GANs) [[arXiv]](https://arxiv.org/abs/1703.00573) 108 | - Generating images with recurrent adversarial networks [[arXiv]](https://arxiv.org/abs/1602.05110) 109 | - Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1406.2661) [[Code]](https://github.com/goodfeli/adversarial) [[Code]](https://github.com/wiseodd/generative-models) 110 | - Generative Adversarial Networks as Variational Training of Energy Based Models [[arXiv]](https://arxiv.org/abs/1611.01799) 111 | - Generative Adversarial Networks with Inverse Transformation Unit [[arXiv]](https://arxiv.org/abs/1709.09354) 112 | - Generative Adversarial Parallelization [[arXiv]](https://arxiv.org/abs/1612.04021) [[Code]](https://github.com/wiseodd/generative-models) 113 | - Generative Adversarial Residual Pairwise Networks for One Shot Learning [[arXiv]](https://arxiv.org/abs/1703.08033) 114 | - Generative Adversarial Structured Networks [[Paper]](https://c4209155-a-62cb3a1a-s-sites.googlegroups.com/site/nips2016adversarial/WAT16_paper_14.pdf) 115 | - Generative Cooperative Net for Image Generation and Data Augmentation [[arXiv]](https://arxiv.org/abs/1705.02887) 116 | - Generative Moment Matching Networks [[arXiv]](https://arxiv.org/abs/1502.02761) [[Code]](https://github.com/yujiali/gmmn) 117 | - Generative Semantic Manipulation with Contrasting GAN [[arXiv]](https://arxiv.org/abs/1708.00315) 118 | - Geometric GAN [[arXiv]](https://arxiv.org/abs/1705.02894) 119 | - Good Semi-supervised Learning that Requires a Bad GAN [[arXiv]](https://arxiv.org/abs/1705.09783) 120 | - Gradient descent GAN optimization is locally stable [[arXiv]](https://arxiv.org/abs/1706.04156) 121 | - How to Train Your DRAGAN [[arXiv]](https://arxiv.org/abs/1705.07215) 122 | - Image Quality Assessment Techniques Show Improved Training and Evaluation of Autoencoder Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1708.02237) 123 | - Improved Semi-supervised Learning with GANs using Manifold Invariances [[arXiv]](https://arxiv.org/abs/1705.08850) 124 | - Improved Techniques for Training GANs [[arXiv]](https://arxiv.org/abs/1606.03498) [[Code]](https://github.com/openai/improved-gan) 125 | - Improved Training of Wasserstein GANs [[arXiv]](https://arxiv.org/abs/1704.00028) [[Code]](https://github.com/wiseodd/generative-models) 126 | - InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets [[arXiv]](https://arxiv.org/abs/1606.03657) [[Code]](https://github.com/wiseodd/generative-models) 127 | - Inverting The Generator Of A Generative Adversarial Network [[Paper]](https://c4209155-a-62cb3a1a-s-sites.googlegroups.com/site/nips2016adversarial/WAT16_paper_9.pdf) 128 | - It Takes (Only) Two: Adversarial Generator-Encoder Networks [[arXiv]](https://arxiv.org/abs/1704.02304) 129 | - KGAN: How to Break The Minimax Game in GAN [[arXiv]](https://arxiv.org/abs/1711.01744) 130 | - Learning in Implicit Generative Models [[Paper]](https://c4209155-a-62cb3a1a-s-sites.googlegroups.com/site/nips2016adversarial/WAT16_paper_10.pdf) 131 | - Learning Loss for Knowledge Distillation with Conditional Adversarial Networks [[arXiv]](https://arxiv.org/abs/1709.00513) 132 | - Learning to Discover Cross-Domain Relations with Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1703.05192) [[Code]](https://github.com/wiseodd/generative-models) 133 | - Learning Texture Manifolds with the Periodic Spatial GAN [[arXiv]](https://arxiv.org/abs/1705.06566) 134 | - Least Squares Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1611.04076) [[Code]](https://github.com/wiseodd/generative-models) 135 | - Linking Generative Adversarial Learning and Binary Classification [[arXiv]](https://arxiv.org/abs/1709.01509) 136 | - Loss-Sensitive Generative Adversarial Networks on Lipschitz Densities [[arXiv]](https://arxiv.org/abs/1701.06264) 137 | - LR-GAN: Layered Recursive Generative Adversarial Networks for Image Generation [[arXiv]](https://arxiv.org/abs/1703.01560) 138 | - MAGAN: Margin Adaptation for Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1704.03817) [[Code]](https://github.com/wiseodd/generative-models) 139 | - Maximum-Likelihood Augmented Discrete Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1702.07983) 140 | - McGan: Mean and Covariance Feature Matching GAN [[arXiv]](https://arxiv.org/abs/1702.08398) 141 | - Message Passing Multi-Agent GANs [[arXiv]](https://arxiv.org/abs/1612.01294) 142 | - MMD GAN: Towards Deeper Understanding of Moment Matching Network [[arXiv]](https://arxiv.org/abs/1705.08584) 143 | - Mode Regularized Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1612.02136) [[Code]](https://github.com/wiseodd/generative-models) 144 | - Multi-Agent Diverse Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1704.02906) 145 | - Multi-Generator Gernerative Adversarial Nets [[arXiv]](https://arxiv.org/abs/1708.02556) 146 | - Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models [[arXiv]](https://arxiv.org/abs/1705.10843) 147 | - On Convergence and Stability of GANs [[arXiv]](https://arxiv.org/abs/1705.07215) 148 | - On the effect of Batch Normalization and Weight Normalization in Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1704.03971) 149 | - On the Quantitative Analysis of Decoder-Based Generative Models [[arXiv]](https://arxiv.org/abs/1611.04273) 150 | - Optimizing the Latent Space of Generative Networks [[arXiv]](https://arxiv.org/abs/1707.05776) 151 | - Parametrizing filters of a CNN with a GAN [[arXiv]](https://arxiv.org/abs/1710.11386) 152 | - PixelGAN Autoencoders [[arXiv]](https://arxiv.org/abs/1706.00531) 153 | - Progressive Growing of GANs for Improved Quality, Stability, and Variation [[arXiv]](https://arxiv.org/abs/1710.10196) [[Code]](https://github.com/tkarras/progressive_growing_of_gans) 154 | - SegAN: Adversarial Network with Multi-scale L1 Loss for Medical Image Segmentation [[arXiv]](https://arxiv.org/abs/1706.01805) 155 | - SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient [[arXiv]](https://arxiv.org/abs/1609.05473) 156 | - Simple Black-Box Adversarial Perturbations for Deep Networks [[Paper]](https://c4209155-a-62cb3a1a-s-sites.googlegroups.com/site/nips2016adversarial/WAT16_paper_11.pdf) 157 | - Softmax GAN [[arXiv]](https://arxiv.org/abs/1704.06191) 158 | - Stabilizing Training of Generative Adversarial Networks through Regularization [[arXiv]](https://arxiv.org/abs/1705.09367) 159 | - Stacked Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1612.04357) 160 | - Statistics of Deep Generated Images [[arXiv]](https://arxiv.org/abs/1708.02688) 161 | - Structured Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1711.00889) 162 | - Tensorizing Generative Adversarial Nets [[arXiv]](https://arxiv.org/abs/1710.10772) 163 | - The Cramer Distance as a Solution to Biased Wasserstein Gradients [[arXiv]](https://arxiv.org/abs/1705.10743) 164 | - Towards Understanding Adversarial Learning for Joint Distribution Matching [[arXiv]](https://arxiv.org/abs/1709.01215) 165 | - Training generative neural networks via Maximum Mean Discrepancy optimization [[arXiv]](https://arxiv.org/abs/1505.03906) 166 | - Triple Generative Adversarial Nets [[arXiv]](https://arxiv.org/abs/1703.02291) 167 | - Unrolled Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1611.02163) 168 | - Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1511.06434) [[Code]](https://github.com/Newmu/dcgan_code) [[Code]](https://github.com/pytorch/examples/tree/master/dcgan) [[Code]](https://github.com/carpedm20/DCGAN-tensorflow) [[Code]](https://github.com/soumith/dcgan.torch) [[Code]](https://github.com/jacobgil/keras-dcgan) 169 | - Wasserstein GAN [[arXiv]](https://arxiv.org/abs/1701.07875) [[Code]](https://github.com/martinarjovsky/WassersteinGAN) [[Code]](https://github.com/wiseodd/generative-models) 170 | 171 | ## Applied Vision 172 | - 3D Object Reconstruction from a Single Depth View with Adversarial Learning [[arXiv]](https://arxiv.org/abs/1708.07969) 173 | - 3D Shape Induction from 2D Views of Multiple Objects [[arXiv]](https://arxiv.org/abs/1612.05872) 174 | - A step towards procedural terrain generation with GANs [[arXiv]](https://arxiv.org/abs/1707.03383) [[Code]](https://github.com/christopher-beckham/gan-heightmaps) 175 | - Abnormal Event Detection in Videos using Generative Adversarial Nets [[arXiv]](https://arxiv.org/abs/1708.09644) 176 | - Adversarial Generation of Training Examples for Vehicle License Plate Recognition [[arXiv]](https://arxiv.org/abs/1707.03124) 177 | - Adversarial nets with perceptual losses for text-to-image synthesis [[arXiv]](https://arxiv.org/abs/1708.09321) 178 | - Adversarial Networks for Spatial Context-Aware Spectral Image Reconstruction from RGB [[arXiv]](https://arxiv.org/abs/1709.00265) 179 | - Adversarial Networks for the Detection of Aggressive Prostate Cancer [[arXiv]](https://arxiv.org/abs/1702.08014) 180 | - Adversarial PoseNet: A Structure-aware Convolutional Network for Human Pose Estimation [[arXiv]](https://arxiv.org/pdf/1705.00389.pdf) 181 | - Adversarial Training For Sketch Retrieval [[arXiv]](https://arxiv.org/abs/1607.02748) 182 | - Aesthetic-Driven Image Enhancement by Adversarial Learning [[arXiv]](https://arxiv.org/abs/1707.05251) 183 | - Age Progression / Regression by Conditional Adversarial Autoencoder [[arXiv]](https://arxiv.org/abs/1702.08423) 184 | - AlignGAN: Learning to Align Cross-Domain Images with Conditional Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1707.01400) 185 | - Amortised MAP Inference for Image Super-resolution [[arXiv]](https://arxiv.org/abs/1610.04490) 186 | - Analyzing Perception-Distortion Tradeoff using Enhanced Perceptual Super-resolution Network [[arXiv]](https://arxiv.org/abs/1811.00344) [[Code]](https://github.com/subeeshvasu/2018_subeesh_epsr_eccvw) 187 | - A Novel Approach to Artistic Textual Visualization via GAN [[arXiv]](https://arxiv.org/abs/1710.10553) 188 | - Anti-Makeup: Learning A Bi-Level Adversarial Network for Makeup-Invariant Face Verification [[arXiv]](https://arxiv.org/abs/1709.03654) 189 | - Arbitrary Facial Attribute Editing: Only Change What You Want [[arXiv]](https://arxiv.org/abs/1711.10678) [[Code]](https://github.com/LynnHo/AttGAN-Tensorflow) 190 | - ARIGAN: Synthetic Arabidopsis Plants using Generative Adversarial Network [[arXiv]](https://arxiv.org/abs/1709.00938) 191 | - ArtGAN: Artwork Synthesis with Conditional Categorial GANs [[arXiv]](https://arxiv.org/abs/1702.03410) 192 | - Artificial Generation of Big Data for Improving Image Classification: A Generative Adversarial Network Approach on SAR Data [[arXiv]](https://arxiv.org/abs/1711.02010) 193 | - Auto-Encoder Guided GAN for Chinese Calligraphy Synthesis [[arXiv]](https://arxiv.org/abs/1706.08789) 194 | - Auto-painter: Cartoon Image Generation from Sketch by Using Conditional Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1705.01908) 195 | - Automatic Liver Segmentation Using an Adversarial Image-to-Image Network [[arXiv]](https://arxiv.org/abs/1707.08037) 196 | - Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View Synthesis [[arXiv]](https://arxiv.org/abs/1704.04086) 197 | - CAN: Creative Adversarial Networks Generating “Art” by Learning About Styles and Deviating from Style Norms [[arXiv]](https://arxiv.org/abs/1706.07068) 198 | - CompoNet: Learning to Generate the Unseen by Part Synthesis and Composition [[arXiv]](https://arxiv.org/abs/1811.07441) [[Code]](https://github.com/nschor/CompoNet) 199 | - Compressed Sensing MRI Reconstruction with Cyclic Loss in Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1709.00753) 200 | - Conditional Adversarial Network for Semantic Segmentation of Brain Tumor [[arXiv]](https://arxiv.org/abs/1708.05227) 201 | - Conditional generative adversarial nets for convolutional face generation [[Paper]](http://www.foldl.me/uploads/2015/conditional-gans-face-generation/paper.pdf) 202 | - Conditional Image Synthesis with Auxiliary Classifier GANs [[Paper]](https://c4209155-a-62cb3a1a-s-sites.googlegroups.com/site/nips2016adversarial/WAT16_paper_7.pdf) [[arXiv]](https://arxiv.org/abs/1610.09585) [[Code]](https://github.com/wiseodd/generative-models) 203 | - Contextual RNN-GANs for Abstract Reasoning Diagram Generation [[arXiv]](https://arxiv.org/abs/1609.09444) 204 | - Controllable Generative Adversarial Network [[arXiv]](https://arxiv.org/abs/1708.00598) 205 | - Creatism: A deep-learning photographer capable of creating professional work [[arXiv]](https://arxiv.org/abs/1707.03491) 206 | - Crossing Nets: Combining GANs and VAEs with a Shared Latent Space for Hand Pose Estimation [[arXiv]](https://arxiv.org/abs/1702.03431) 207 | - CVAE-GAN: Fine-Grained Image Generation through Asymmetric Training [[arXiv]](https://arxiv.org/abs/1703.10155) 208 | - Data Augmentation in Classification using GAN [[arXiv]](https://arxiv.org/abs/1711.00648) 209 | - Deep Generative Adversarial Compression Artifact Removal [[arXiv]](https://arxiv.org/abs/1704.02518) 210 | - Deep Generative Adversarial Networks for Compressed Sensing (GANCS) Automates MRI [[arXiv]](https://arxiv.org/abs/1706.00051) 211 | - Deep Generative Adversarial Neural Networks for Realistic Prostate Lesion MRI Synthesis [[arXiv]](https://arxiv.org/abs/1708.00129) 212 | - Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks [[arXiv]](https://arxiv.org/abs/1506.05751) [[Code]](https://github.com/facebook/eyescream) [[Blog]](http://soumith.ch/eyescream/) 213 | - Deep multi-scale video prediction beyond mean square error [[arXiv]](https://arxiv.org/abs/1511.05440) [[Code]](https://github.com/dyelax/Adversarial_Video_Generation) 214 | - Deep Unsupervised Representation Learning for Remote Sensing Images [[arXiv]](https://arxiv.org/abs/1612.08879) 215 | - DeLiGAN : Generative Adversarial Networks for Diverse and Limited Data [[arXiv]](https://arxiv.org/abs/1706.02071) 216 | - Depth Structure Preserving Scene Image Generation [[arXiv]](https://arxiv.org/abs/1706.00212) 217 | - DualGAN: Unsupervised Dual Learning for Image-to-Image Translation [[arXiv]](https://arxiv.org/abs/1704.02510) [[Code]](https://github.com/wiseodd/generative-models) 218 | - Dual Motion GAN for Future-Flow Embedded Video Prediction [[arXiv]](https://arxiv.org/abs/1708.00284) 219 | - Efficient Super Resolution For Large-Scale Images Using Attentional GAN [[arXiv]](https://arxiv.org/abs/1812.04821) [[Thesis]](https://digitalcommons.wpi.edu/etd-theses/1256/) [[Thesis]](https://www.wpi.edu/news/announcements/data-science-ms-thesis-presentation-xiaozhou-zou) 220 | - ExprGAN: Facial Expression Editing with Controllable Expression Intensity [[arXiv]](https://arxiv.org/abs/1709.03842) 221 | - Face Aging With Conditional Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1702.01983) 222 | - Face Transfer with Generative Adversarial Network [[arXiv]](https://arxiv.org/abs/1710.06090) 223 | - Filmy Cloud Removal on Satellite Imagery with Multispectral Conditional Generative Adversarial Nets [[arXiv]](https://arxiv.org/abs/1710.04835) 224 | - Freehand Ultrasound Image Simulation with Spatially-Conditioned Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1707.05392) 225 | - From source to target and back: symmetric bi-directional adaptive GAN [[arXiv]](https://arxiv.org/abs/1705.08824) 226 | - Full Resolution Image Compression with Recurrent Neural Networks [[arXiv]](https://arxiv.org/abs/1608.05148) 227 | - GANs for Biological Image Synthesis [[arXiv]](https://arxiv.org/abs/1708.04692) 228 | - GeneGAN: Learning Object Transfiguration and Attribute Subspace from Unpaired Data [[arXiv]](https://arxiv.org/abs/1705.04932) [[Code]](https://github.com/Prinsphield/GeneGAN) 229 | - Generate Identity-Preserving Faces by Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1706.03227) 230 | - Generate To Adapt: Aligning Domains using Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1704.01705) 231 | - Generative Adversarial Graph Convolutional Networks for Human Action Synthesis [[arXiv]](https://arxiv.org/abs/2110.11191) [[Code]](https://github.com/DegardinBruno/Kinetic-GAN) 232 | - Generative Adversarial Models for People Attribute Recognition in Surveillance [[arXiv]](https://arxiv.org/abs/1707.02240) 233 | - Generative Adversarial Network based on Resnet for Conditional Image Restoration [[arxiv]](https://arxiv.org/abs/1707.04881) 234 | - Generative Adversarial Network-based Synthesis of Visible Faces from Polarimetric Thermal Faces [[arXiv]](https://arxiv.org/abs/1708.02681) 235 | - Generative Adversarial Networks for Multimodal Representation Learning in Video Hyperlinking [[arXiv]](https://arxiv.org/abs/1705.05103) 236 | - Generative Adversarial Text to Image Synthesis [[arXiv]](https://arxiv.org/abs/1605.05396) [[Code]](https://github.com/paarthneekhara/text-to-image) 237 | - Generative Visual Manipulation on the Natural Image Manifold [[Project]](http://www.eecs.berkeley.edu/~junyanz/projects/gvm/) [[Youtube]](https://youtu.be/9c4z6YsBGQ0) [[Paper]](https://arxiv.org/abs/1609.03552) [[Code]](https://github.com/junyanz/iGAN) 238 | - Global-to-Local Generative Model for 3D Shapes [[Project]](http://vcc.szu.edu.cn/research/2018/G2L)[[Code]](https://github.com/Hao-HUST/G2LGAN) 239 | - GP-GAN: Gender Preserving GAN for Synthesizing Faces from Landmarks [[arXiv]](https://arxiv.org/abs/1710.00962) 240 | - GP-GAN: Towards Realistic High-Resolution Image Blending [[arXiv]](https://arxiv.org/abs/1703.07195) 241 | - Guiding InfoGAN with Semi-Supervision [[arXiv]](https://arxiv.org/abs/1707.04487) 242 | - How to Fool Radiologists with Generative Adversarial Networks? A Visual Turing Test for Lung Cancer Diagnosis [[arXiv]](https://arxiv.org/abs/1710.09762) 243 | - Hierarchical Detail Enhancing Mesh-Based Shape Generation with 3D Generative Adversarial Network [[arXiv]](https://arxiv.org/abs/1709.07581) 244 | - High-Quality Face Image SR Using Conditional Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1707.00737) 245 | - High-Quality Facial Photo-Sketch Synthesis Using Multi-Adversarial Networks [[arXiv]](https://arxiv.org/abs/1710.10182) 246 | - Image De-raining Using a Conditional Generative Adversarial Network [[arXiv]](https://arxiv.org/abs/1701.05957) 247 | - Image Generation and Editing with Variational Info Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1701.04568) 248 | - Image-to-Image Translation with Conditional Adversarial Networks [[arXiv]](https://arxiv.org/abs/1611.07004) [[Code]](https://github.com/phillipi/pix2pix) 249 | - Improved Adversarial Systems for 3D Object Generation and Reconstruction [[arXiv]](https://arxiv.org/abs/1707.09557) [[Code]](https://github.com/EdwardSmith1884/3D-IWGAN) 250 | - Improving Heterogeneous Face Recognition with Conditional Adversarial Networks [[arXiv]](https://arxiv.org/abs/1709.02848) 251 | - Improving image generative models with human interactions [[arXiv]](https://arxiv.org/abs/1709.10459) 252 | - Imitating Driver Behavior with Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1701.06699) 253 | - Interactive 3D Modeling with a Generative Adversarial Network [[arXiv]](https://arxiv.org/abs/1706.05170) 254 | - Intraoperative Organ Motion Models with an Ensemble of Conditional Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1709.02255) 255 | - Invertible Conditional GANs for image editing [[arXiv]](https://arxiv.org/abs/1611.06355) [[Paper]](https://c4209155-a-62cb3a1a-s-sites.googlegroups.com/site/nips2016adversarial/WAT16_paper_8.pdf) 256 | - Joint Discriminative and Generative Learning for Person Re-identification [[Project]](http://zdzheng.xyz/DG-Net/) [[Paper]](https://arxiv.org/abs/1904.07223) [[YouTube]](https://www.youtube.com/watch?v=ubCrEAIpQs4) [[Bilibili]](https://www.bilibili.com/video/av51439240) [[Poster]](http://zdzheng.xyz/images/DGNet_poster.pdf) [[Code]](https://github.com/NVlabs/DG-Net) 257 | - Label Denoising Adversarial Network (LDAN) for Inverse Lighting of Face Images [[arXiv]](https://arxiv.org/abs/1709.01993) 258 | - Learning a Driving Simulator [[arXiv]](https://arxiv.org/abs/1608.01230) 259 | - Learning a Generative Adversarial Network for High Resolution Artwork Synthesis [[arXiv]](https://arxiv.org/abs/1708.09533) 260 | - Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling [[arXiv]](https://arxiv.org/abs/1610.07584) 261 | - Learning from Simulated and Unsupervised Images through Adversarial Training [[arXiv]](https://arxiv.org/abs/1612.07828) 262 | - Learning to Discover Cross-Domain Relations with Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1703.05192) 263 | - Learning to Generate Chairs with Generative Adversarial Nets [[arXiv]](https://arxiv.org/abs/1705.10413) 264 | - Learning to Generate Time-Lapse Videos Using Multi-Stage Dynamic Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1709.07592) 265 | - Low Dose CT Image Denoising Using a Generative Adversarial Network with Wasserstein Distance and Perceptual Loss [[arXiv]](https://arxiv.org/abs/1708.00961) 266 | - MARTA GANs: Unsupervised Representation Learning for Remote Sensing Image Classification [[arXiv]](https://arxiv.org/abs/1612.08879) 267 | - Megapixel Size Image Creation using Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1706.00082) 268 | - Microscopy Cell Segmentation via Adversarial Neural Networks [[arXiv]](https://arxiv.org/abs/1709.05860) 269 | - MoCoGAN: Decomposing Motion and Content for Video Generation [[arXiv]](https://arxiv.org/abs/1707.04993) 270 | - Multi-view Generative Adversarial Networks [[Paper]](https://c4209155-a-62cb3a1a-s-sites.googlegroups.com/site/nips2016adversarial/WAT16_paper_13.pdf) 271 | - Neural Photo Editing with Introspective Adversarial Networks [[Paper]](https://c4209155-a-62cb3a1a-s-sites.googlegroups.com/site/nips2016adversarial/WAT16_paper_15.pdf) [[arXiv]](https://arxiv.org/abs/1609.07093) 272 | - Neural Stain-Style Transfer Learning using GAN for Histopathological Images [[arXiv]](https://arxiv.org/abs/1710.08543) 273 | - Outline Colorization through Tandem Adversarial Networks [[arXiv]](https://arxiv.org/abs/1704.08834) 274 | - Perceptual Adversarial Networks for Image-to-Image Transformation [[arXiv]](https://arxiv.org/abs/1706.09138) 275 | - Perceptual Generative Adversarial Networks for Small Object Detection [[arXiv]](https://arxiv.org/abs/1706.05274) 276 | - Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network [[arXiv]](https://arxiv.org/abs/1609.04802) 277 | - Pose Guided Person Image Generation [[arXiv]](https://arxiv.org/abs/1705.09368) 278 | - Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1604.04382) 279 | - Recurrent Topic-Transition GAN for Visual Paragraph Generation [[arXiv]](https://arxiv.org/abs/1703.07022) 280 | - RenderGAN: Generating Realistic Labeled Data [[arXiv]](https://arxiv.org/abs/1611.01331) 281 | - Representation Learning and Adversarial Generation of 3D Point Clouds [[arXiv]](https://arxiv.org/abs/1707.02392) 282 | - Retinal Vasculature Segmentation Using Local Saliency Maps and Generative Adversarial Networks For Image Super Resolution [[arXiv]](https://arxiv.org/abs/1710.04783) 283 | - Retinal Vessel Segmentation in Fundoscopic Images with Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1706.09318) 284 | - SAD-GAN: Synthetic Autonomous Driving using Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1611.08788) 285 | - SalGAN: Visual Saliency Prediction with Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1701.01081v2) 286 | - SegAN: Adversarial Network with Multi-scale L1 Loss for Medical Image Segmentation [[arXiv]](https://arxiv.org/abs/1706.01805) 287 | - SeGAN: Segmenting and Generating the Invisible [[arXiv]](https://arxiv.org/abs/1703.10239) 288 | - Semantic Image Inpainting with Deep Generative Models [[arXiv]](https://arxiv.org/abs/1607.07539) 289 | - EdgeConnect: Generative Image Inpainting with Adversarial Edge Learning [[arXiv]](https://arxiv.org/abs/1901.00212) [[Code]](https://github.com/knazeri/edge-connect) 290 | - Semantic Image Synthesis via Adversarial Learning [[arXiv]](https://arxiv.org/abs/1707.06873) 291 | - Semantic Segmentation using Adversarial Networks [[arXiv]](https://arxiv.org/abs/1611.08408) 292 | - Semantically Decomposing the Latent Spaces of Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1705.07904) 293 | - Semi-Latent GAN: Learning to generate and modify facial images from attributes [[arXiv]](https://arxiv.org/abs/1704.02166) 294 | - Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1611.06430) 295 | - Sharpness-aware Low dose CT denoising using conditional generative adversarial network [[arXiv]](https://arxiv.org/abs/1708.06453) 296 | - Simultaneously Color-Depth Super-Resolution with Conditional Generative Adversarial Network [[arXiv]](https://arxiv.org/abs/1708.09105) 297 | - SingleGAN: Image-to-Image Translation by a Single-Generator Network using Multiple Generative Adversarial Learning [[arXiv]](https://arxiv.org/abs/1810.04991) [[Code]](https://github.com/Xiaoming-Yu/SingleGAN) 298 | - Socially-compliant Navigation through Raw Depth Inputs with Generative Adversarial Imitation Learning [[arXiv]](https://arxiv.org/abs/1710.02543) 299 | - StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1612.03242) 300 | - StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1710.10916) 301 | - Style Transfer for Sketches with Enhanced Residual U-net and Auxiliary Classifier GAN [[arXiv]](https://arxiv.org/abs/1706.03319) 302 | - Supervised Adversarial Networks for Image Saliency Detection [[arXiv]](https://arxiv.org/abs/1704.07242) 303 | - Synthesis of Positron Emission Tomography (PET) Images via Multi-channel Generative Adversarial Networks (GANs) [[arXiv]](https://arxiv.org/abs/1707.09747) 304 | - Synthesizing Filamentary Structured Images with GANs [[arXiv]](https://arxiv.org/abs/1706.02185) 305 | - Synthetic Iris Presentation Attack using iDCGAN [[arXiv]](https://arxiv.org/abs/1710.10565) 306 | - Synthetic Medical Images from Dual Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1709.01872) 307 | - TAC-GAN - Text Conditioned Auxiliary Classifier Generative Adversarial Network [[arXiv]](https://arxiv.org/abs/1703.06412) 308 | - Temporal Generative Adversarial Nets with Singular Value Clipping [[arXiv]](https://arxiv.org/abs/1611.06624) 309 | - TextureGAN: Controlling Deep Image Synthesis with Texture Patches [[arXiv]](https://arxiv.org/abs/1706.02823) 310 | - Texture Synthesis with Spatial Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1611.08207v3) [[Code]](https://github.com/ubergmann/spatial_gan) 311 | - Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language [[arXiv]](https://arxiv.org/abs/1810.11919) [[Code]](https://github.com/woozzu/tagan) 312 | - The Conditional Analogy GAN: Swapping Fashion Articles on People Images [[arXiv]](https://arxiv.org/abs/1709.04695) 313 | - TopoAL: An Adversarial Learning Approach for Topology-Aware Road Segmentation [[Paper]](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123720222.pdf) 314 | - TopoGAN: A Topology-Aware Generative Adversarial Network [[Paper]](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123480120.pdf) 315 | - Towards Adversarial Retinal Image Synthesis [[arXiv]](https://arxiv.org/abs/1701.08974) [[Code]](https://github.com/costapt/vess2ret) [[Demo]](http://vess2ret.inesctec.pt/retina) 316 | - Towards Diverse and Natural Image Descriptions via a Conditional GAN [[arXiv]](https://arxiv.org/abs/1703.06029) 317 | - Towards the Automatic Anime Characters Creation with Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1708.05509) 318 | - UGAN: Enhancing Underwater Imagery using Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1801.04011) 319 | - Unlabeled Samples Generated by GAN Improve the Person Re-identification Baseline in vitro [[arXiv]](https://arxiv.org/abs/1701.07717)[[Code]](https://github.com/layumi/Person-reID_GAN) 320 | - Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks [[arXiv]](https://arxiv.org/abs/1703.10593) 321 | - Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1511.06390) 322 | - Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery [[arXiv]](https://arxiv.org/abs/1703.05921) 323 | - Unsupervised Cross-Domain Image Generation [[arXiv]](https://arxiv.org/abs/1611.02200) 324 | - Unsupervised Diverse Colorization via Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1702.06674) 325 | - Unsupervised Pixel–Level Domain Adaptation with Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1612.05424) 326 | - Unsupervised Visual Attribute Transfer with Reconfigurable Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1707.09798) 327 | - VIGAN: Missing View Imputation with Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1708.06724) 328 | - WaterGAN: Unsupervised Generative Network to Enable Real-time Color Correction of Monocular Underwater Images [[arXiv]](https://arxiv.org/abs/1702.07392) 329 | - Weakly Supervised Generative Adversarial Networks for 3D Reconstruction [[arXiv]](https://arxiv.org/abs/1705.10904) 330 | - [TomoGAN: Low-Dose X-Ray Tomography with Generative Adversarial Networks] [[scholar]](https://scholar.google.ca/scholar?hl=en&as_sdt=0%2C5&q=TomoGAN%3A+Low-Dose+X-Ray+Tomography+with+Generative+Adversarial+Networks&btnG=) [[arXiv]](https://arxiv.org/abs/1902.07582) 331 | 332 | ## Applied Other 333 | - Adversarial Generation of Natural Language [[arXiv]](https://arxiv.org/abs/1705.10929) 334 | - Adversarial Ranking for Language Generation [[arXiv]](https://arxiv.org/abs/1705.11001) 335 | - Adversarial Training Methods for Semi-Supervised Text Classification [[arXiv]](https://arxiv.org/abs/1605.07725) [[Paper]](https://c4209155-a-62cb3a1a-s-sites.googlegroups.com/site/nips2016adversarial/WAT16_paper_12.pdf) 336 | - A Generative Model for Volume Rendering [[arXiv]](A Generative Model for Volume Rendering) 337 | - ChemGAN challenge for drug discovery: can AI reproduce natural chemical diversity? [[arXiv]](https://arxiv.org/abs/1708.08227) 338 | - Generating Adversarial Malware Examples for Black-Box Attacks Based on GAN [[arXiv]](https://arxiv.org/abs/1702.05983) 339 | - Generating Multi-label Discrete Electronic Health Records using Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1703.06490) 340 | - Language Generation with Recurrent Generative Adversarial Networks without Pre-training [[arXiv]](https://arxiv.org/abs/1706.01399) 341 | - Learning to Protect Communications with Adversarial Neural Cryptography [[arXiv]](https://arxiv.org/abs/1610.06918) [[Blog]](https://blog.acolyer.org/2017/02/10/learning-to-protect-communications-with-adversarial-neural-cryptography/) 342 | - Long Text Generation via Adversarial Training with Leaked Information [[arXiv]](https://arxiv.org/abs/1709.08624) 343 | - MidiNet: A Convolutional Generative Adversarial Network for Symbolic-domain Music Generation using 1D and 2D Conditions [[arXiv]](https://arxiv.org/abs/1703.10847) 344 | - MuseGAN: Symbolic-domain Music Generation and Accompaniment with Multi-track Sequential Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1709.06298) 345 | - Reconstruction of three-dimensional porous media using generative adversarial neural networks [[arXiv]](https://arxiv.org/abs/1704.03225) [[Code]](https://github.com/LukasMosser/PorousMediaGan) 346 | - SEGAN: Speech Enhancement Generative Adversarial Network [[arXiv]](https://arxiv.org/abs/1703.09452) 347 | - Semi-supervised Learning of Compact Document Representations with Deep Networks [[Paper]](http://www.cs.nyu.edu/~ranzato/publications/ranzato-icml08.pdf) 348 | - SSGAN: Secure Steganography Based on Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1707.01613) 349 | - Steganographic Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1703.05502) 350 | - Towards Grounding Conceptual Spaces in Neural Representations [[arXiv]](https://arxiv.org/abs/1706.04825) 351 | 352 | ## Humor 353 | - Stopping GAN Violence: Generative Unadversarial Networks [[arXiv]](https://arxiv.org/abs/1703.02528) 354 | --------------------------------------------------------------------------------